Resultados de investigación

Currently, the Web has revolutionized our daily life, has become a source of information, knowledge, source of consultation and provision of services in various areas. On the other hand, through the Internet, you easily get information from any type of institution, and the first impression you have about an organization is almost always based on your website. The digitization of education-related services is increasingly frequent, related to educational resources, guides, books, online courses and various services that allow the improvement and continuous updating of teachers and students. Therefore, it is important that users, regardless of their disabilities, access these websites and university services in an effective, efficient and satisfactory manner. However, websites of universities in Latin America, still do not meet the criteria of web accessibility. This study describes the web accessibility problems identified in 348 websites of the main universities in Latin America according to the Webometrics ranking. The results showed that the websites of the universities of Brazil, Mexico, Colombia, Peru and Ecuador have frequent errors related to the criterion of success 1.1.1 that refers to the “Non-text Content” of Level A, in which there is a lack of alternative text in the images. It was found that the websites of the universities included in this study violate the web accessibility requirements in accordance with the Web Content Accessibility Guidelines (WCAG) 2.0. In the evaluation process, the Website Accessibility Conformance Evaluation Methodology was applied, to identify the ease with which a website can be accessed in accordance with WCAG 2.0 standards. This study presents several barriers to accessibility, which is why it is necessary to strengthen the legislation in each country and to share best web accessibility practices so that websites are more accessible and inclusive.

Enter the RobotriX, an extremely photorealistic indoor dataset designed to enable the application of deep learning techniques to a wide variety of robotic vision problems. The RobotriX consists of hyperrealistic indoor scenes which are explored by robot agents which also interact with objects in a visually realistic manner in that simulated world. Photorealistic scenes and robots are rendered by Unreal Engine into a virtual reality headset which captures gaze so that a human operator can move the robot and use controllers for the robotic hands; scene information is dumped on a per-frame basis so that it can be reproduced offline using UnrealCV to generate raw data and ground truth labels. By taking this approach we were able to generate a dataset of 38 semantic classes across 512 sequences totaling 8M stills recorded at +60 frames per second with full HD resolution. For each frame, RGB-D and 3D information is provided with full annotations in both spaces. Thanks to the high quality and quantity of both raw information and annotations, the RobotriX will serve as a new milestone for investigating 2D and 3D robotic vision tasks with large-scale data-driven techniques.

Son los datos extraídos del software ATLAS.ti 24, del análisis del largometraje Barbie (2023).

Encuesta compuesta por un conjunto de sencillas cuestiones cuyo objetivo es la valoración cuantificada del estado actual (madurez) en Buen Gobierno y Gobierno TI en la Universidad de Alicante, fundamentalmente como consecuencia de la aplicación del modelo de cartera estratégica de proyectos TI: priorización estratégica de proyectos + gobernanza de la ejecución + analisis de los resultados.

This study presents the results of a systematic literature review on the combined field of Accessibility and Massive Open Online Courses (MOOCs), covering the time period from 2008 to 2016 July. This dataset updates the previous release from 2008 to 2016 May (http://hdl.handle.net/10045/54846).

We analyze and compare the advertising by food brands on regular TV networks (traditional advertising) with videos by child YouTubers (influencing) in Spanish. An exploratory study is conducted by means of a content analysis of 304 videos, with 22 variables grouped into 4 categories: obesogenic features, innovative trends, prevalence of ultra-processed vs. healthy products in advertising, and marketing style.

Se ha realizado la caracterización colorimétrica de cuatro pantallas Retina correspondientes a tres modelos de iPad: iPad4 (2013), iPadAir (2014), iPad17 (2017) e iPad19 (2019). Dicha caracterización se ha llevado a cabo mediante la medida experimental de los valores triestímulo de 1000 colores y una posterior interpolación hasta el conjunto de colores reproducibles en la pantalla. Los colores medidos son el resultado de una matriz de 10x10x10 niveles digitales de encendido de los pixeles de cada pantalla (canales Rojo-Verde-Azul). Para cada uno de los dispositivos se han construido dos ficheros de datos (.mat) que contiene las siguientes variables: • posxy: coordenadas del punto de la pantalla del dispositivo donde se han realizado las medidas experimentales de los valores triestímulo, con origen en el centro de la pantalla, • x e y: matrices de coordenadas espaciales de cada pixel de la pantalla, en este caso 2048x1536 pixeles para las 3 pantallas, • tablaLUT: tabla 3DLUT calculada por interpolación lineal o cúbica a partir de las 1000 medidas experimentales y compuesta por 16777216x6 datos. Cada fila corresponde a un color de los 2563 posibles (256 niveles digitales por canal, 3 canales). Las tres primeras columnas recogen los niveles digitales de cada color, normalizados entre 0 y 1. Las tres últimas columnas corresponden a los valores triestímulo XYZ de ese color.

The Green Corpus of Vegan and Vegetarian Product Names is a specialized, open-access linguistic corpus designed to collect, categorize, and analyze the creative naming and word-formation strategies used in plant-based products. The initial version of the dataset consists of written digital data compiled between August 2024 and August 2025 from various vegan and vegetarian websites, comprising 1,715 product names across 55 distinct brands, from which a focused subset of 563 products was selected for specific analysis. This corpus serves as the empirical foundation for the study "The Green Corpus: A Study of Vegan and Vegetarian Product Names," accepted for publication in NAMES: A Journal of Onomastics. This repository represents the baseline version of the corpus. The dataset is intended to be progressively updated with new market entries and remains open to international collaborations for expansion into additional product categories and languages. The data is accessible for research purposes upon request.